ORIGINAL PAPER
3D Training Control® for football training tasks: intra- and inter-observer reliability of a structural task-classification system
1
University of Coimbra, CIPER, FCDEFUC, Coimbra, Portugal
2
Faculty of Sport Sciences and Physical Education, University of Coimbra, Coimbra, Portugal
3
Deporte y Actividad Física, Instituto Nacional del Fútbol, Instituto Nacional del Fútbol Deporte y Actividad Física (INAF), Santiago, Chile
4
Applied Research Institute (i2A), Polytechnic University of Coimbra, Coimbra, Portugal
5
Sport Physical Activity and Health Research and Innovation Center, Coimbra, Portugal
6
Department of Biomechanics and Sport Engineering, Gdansk University of Physical Education and Sport, Gdansk, Poland
7
Department of Sport and Exercise Science, Institute of Sport, Manchester Metropolitan University, Manchester, United Kingdom
8
Facultad de Educación, Escuela de Ciencias de la Educación y Tecnología, Pedagogía en Educación Física, Universidad Católica Silva Henríquez (UCSH), Santiago, Chile
9
Facultad de Ciencias de la Vida, Universidad de Viña del Mar, Viña del Mar, Chile
Submission date: 2026-03-09
Acceptance date: 2026-05-22
Online publication date: 2026-08-31
Corresponding author
Joel Barrera-Díaz
Faculty of Sport Sciences and Physical Education, University of Coimbra, Santa Clara, Pavilion 3, 3040-248 Coimbra, Portugal
Faculty of Sport Sciences and Physical Education, University of Coimbra, Santa Clara, Pavilion 3, 3040-248 Coimbra, Portugal
KEYWORDS
TOPICS
ABSTRACT
Purpose:
This study examined the intra- and inter-observer reliability of the 3D Training Control® (3D-TC) web-based tool for classifying structural characteristics of football training tasks and deriving a Structural Specificity Index (SSI) score.
Methods:
One-hundred thirteen drills from a professional team’s 2023 season were evaluated using ten predefined criteria grounded in the game’s internal logic. Inter-rater agreement was assessed using Cohen’s kappa, and reliability was quantified using intraclass correlation coefficients (two-way mixed-effects model, mean rating, absolute agreement, 95% confidence intervals) for intra- and inter-observer comparisons.
Results:
Results showed high agreement and excellent reliability across all ten criteria for both observers and across time points. These findings support the reliability of the structural task-classification system embedded in the 3D-TC tool.
Conclusions:
Further studies are required to establish the construct and criterion validity of the resulting index, including its relationship with physiological and external-load metrics and performance-related outcomes.
This study examined the intra- and inter-observer reliability of the 3D Training Control® (3D-TC) web-based tool for classifying structural characteristics of football training tasks and deriving a Structural Specificity Index (SSI) score.
Methods:
One-hundred thirteen drills from a professional team’s 2023 season were evaluated using ten predefined criteria grounded in the game’s internal logic. Inter-rater agreement was assessed using Cohen’s kappa, and reliability was quantified using intraclass correlation coefficients (two-way mixed-effects model, mean rating, absolute agreement, 95% confidence intervals) for intra- and inter-observer comparisons.
Results:
Results showed high agreement and excellent reliability across all ten criteria for both observers and across time points. These findings support the reliability of the structural task-classification system embedded in the 3D-TC tool.
Conclusions:
Further studies are required to establish the construct and criterion validity of the resulting index, including its relationship with physiological and external-load metrics and performance-related outcomes.
REFERENCES (42)
1.
Ramírez Lucas JM, Párraga Montilla JA, Cabrera Linares JC, Latorre Román P. Enhancing physical and cognitive performance in youth football: the role of specific dual-task training. J Funct Morphol Kinesiol. 2025;10(4):404; doi: 10.3390/jfmk10040404.
2.
Marques Filho CV, Montagner PC, Magno Ribas JF. Motor praxeology and soccer: internal logic and indications to the teaching-learning-training process [in Portuguese]. Educ Fis Cienc. 2020;22(2):e126; doi: 10.24215/23142561e126.
3.
Ehmann P, Beavan A, Spielmann J, Mayer J, Altmann S, Ruf L, Rohrmann S, Irmer JP, Englert C. Perceptual-cognitive performance of youth soccer players in a 360-environment: differences between age groups and performance levels. Psychol Sport Exerc. 2022;59:102120; doi: 10.1016/j.psychsport.2021.102120.
4.
Sarmento H, Martinho DV, Gouveia ÉR, Afonso J, Chmura P, Field A, Ordoñez Savedra N, Oliveira R, Praça G, Silva R, Barrera-Díaz J, Clemente FM. The influence of playing position on physical, physiological, and technical demands in adult male soccer matches: a systematic scoping review with evidence gap map. Sports Med. 2024;54(11):2841–64; doi:10.1007/s40279-024-02088-z.
5.
Rennie MJ, Kelly SJ, Bush S, Spurrs RW, Austin DJ, Watsford ML. Phases of match-play in professional Australian Football: distribution of physical and technical performance. J Sports Sci. 2020;38(14):1682–29; doi: 10.1080/02640414.2020.1754726.
6.
Trecroci A, Boccolini G, Duca M, Formenti D, Alberti G. Mental fatigue impairs physical activity, technical and decision-making performance during small-sided games. PLOS ONE. 2020;15(9):e0238461; doi: 10.1371/journal.pone.0238461.
7.
Clemente FM. Small-sided and conditioned games in soccer training: the science and practical applications. Singapore: Springer; 2016.
8.
Casamichana D, Ulloa I, Agirrezabalaga O, Etxeazarra I, González de Suso JM, Azurza A, Calzon B, Arrieta JM, Sasiain I, Ollora J, Barba E, Erkizia B, Lazkano A, Clemente FM, Castellano J. Can we replicate the most demanding periods of official football matches in large-sided training games?. J Funct Morphol Kinesiol. 2025;10(4):410; doi: 10.3390/jfmk10040410.
9.
Woods CT, McKeown I, Rothwell M, Araújo D, Robertson S, Davids K. Sport practitioners as sport ecology designers: how ecological dynamics has progressively changed perceptions of skill “acquisition” in the sporting habitat. Front Psychol. 2020;11:654; doi: 10.3389/fpsyg.2020.00654.
10.
Vaughan J, Mallett CJ, Davids K, Potrac P, López-Felip MA. Developing creativity to enhance human potential in sport: a wicked transdisciplinary challenge. Front Psychol. 2019;10:2090; doi: 10.3389/fpsyg.2019.02090.
11.
Lavega-Burgués P, Magno-Ribas JF, Pic M. Editorial: traditional sporting games and play in physical education: enhancing cultural diversity, emotional well-being, interpersonal relationships and intelligent decisions, volume II. Front Psycol. 2023;14:1302853; doi: 10.3389/fpsyg.2023.1302853.
12.
Menezes-Fagundes F, Magno Ribas JF, Salas-Santandreu C, Lavega-Burgués P. Teaching for understanding the internal logic of sports: a perspective based on teaching games for understanding and motor praxiology. Movimento. 2021;27:e27079; doi: 10.22456/1982-8918.116643.
13.
Zanetti V, Aoki MS, Bradley PS, Moreira A. External and internal training loads for intensive and extensive tactical-conditioning in soccer small sided games. J Hum Kinet. 2022;83:165–73; doi: 10.2478/hukin-2022-0083.
14.
Sarmento H, Clemente FM, Harper LD, da Costa IT, Owen A, Figueiredo AJ. Small sided games in soccer – a systematic review. Int J Perform Anal Sport. 2018;18(5):693–49; doi: 10.1080/24748668.2018.1517288.
15.
Solé J. How is force expressed over time? In: Seirul-lo F (ed.) Training in Team Sports [in Spanish]. Barcelona: Mastercede; 2017, pp. 130–65.
16.
Ibáñez SJ, Feu S, Cañadas M. Integral analysis system of training tasks, SIATE, in invasion games [in Spanish]. E-balonmano.com. 2016;12(1):3–30. Available from: https://www.redalyc.org/articu....
17.
Camenforte I, Casamichana D, Cos F, Castellano J, Fernández J. Design and validation of a specificity level assessment tool for preferential simulation situations in football [in Spanish]. Rev Int Cienc Deporte. 2020;17(63):69–87; doi: 10.5232/ricyde2021.06306.
18.
Díaz Díaz R, Noda de la Nuez R, Arbelo Guerra D. Methodological training proposal in team sports from the elements of internal logic applied to football [in Spanish]. Acción Motriz. 2021;26(1):123–35; doi: 10.65330/am.v26i1.170.
19.
Gabbett TJ, Whyte DG, Hartwig TB, Wescombe H, Naughton GA. The relationship between workloads, physical performance, injury and illness in adolescent male football players. Sports Med. 2014;44(7):989–03; doi: 10.1007/s40279-014-0179-5.
20.
Ribeiro J, Davids K, Araújo D, Guilherme J, Silva P, Garganta J. Exploiting bi-directional self-organizing tendencies in team sports: the role of the game model and tactical principles of play. Front Psychol. 2019;10:2213; doi: 10.3389/fpsyg.2019.02213.
21.
Parlebas P. Games, sport, and societies. Lexicon of motor praxeology [in Spanish]. Editorial Paidotribo; 2008.
22.
Sánchez-López R, Echeazarra I, Castellano J. Comparing semi-professional and amateur game contexts in a Gk+4 vs. 4+Gk via Football Competence (Procedural Tactical Knowledge). Retos. 2023;(47):419–29; doi: 10.47197/retos.v47.94576.
23.
Pinder RA, Davids K, Renshaw I, Araújo D. Representative learning design and functionality of research and practice in sport. J Sport Exerc Psychol. 2011;33(1):146–55; doi: 10.1123/jsep.33.1.146.
24.
Browne PR, Woods CT, Sweeting AJ, Robertson S. Applications of a working framework for the measurement of representative learning design in Australian football. PLOS ONE. 2020;15(11):e0242336; doi: 10.1371/journal.pone.0242336.
25.
Krause L, Farrow D, Pinder RA, Buszard T, Kovalchik S, Reid M. Enhancing skill transfer in tennis using representative learning design. J Sports Sci. 2019;37(22):2560–68; doi: 10.1080/02640414.2019.1647739.
26.
Champion L, Middleton K, MacMahon C. Many pieces to the puzzle: a new holistic workload approach to designing practice in sports. Sports Med Open. 2023;9(1):38; doi: 10.1186/s40798-023-00575-7.
27.
O’Donoghue P. Research methods for sports performance analysis. London: Routledge; 2009; doi: 10.4324/9780203878309.
28.
Cohen J. A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960;20(1):37–46; doi: 10.1177/001316446002000104.
29.
Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–63; doi: 10.1016/j.jcm.2016.02.012.
30.
Sullivan GM. A primer on the validity of assessment instruments. J Grad Med Educ. 2011;3(2):119–20; doi: 10.4300/jgme-d-11-00075.1.
31.
Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231–40; doi: 10.1519/15184.1.
32.
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74; doi: 10.2307/2529310.
33.
Rau G, Shih Y-S. Evaluation of Cohen’s kappa and other measures of inter-rater agreement for genre analysis and other nominal data. J Engl Acad Purp. 2021;53:101026; doi: 10.1016/j.jeap.2021.101026.
34.
Gan X, Fernandez IC, Guo J, Wilson M, Zhao Y, Zhou B, Zhou B, Wu J. When to use what: methods for weighting and aggregating sustainability indicators. Ecolog Indic. 2017;81:491–502; doi: 10.1016/j.ecolind.2017.05.068.
35.
Nardo M, Saisana M, Saltelli A, Tarantola S. Tools for composite indicators building. European Comission: Joint Research Centre Publication; 2005. Available from: https://publications.jrc.ec.eu... (accessed 10.02.2026).
36.
Warneke K, Gronwald T, Wallot S, Magno A, Hillebrecht M, Wirth K. Discussion on the validity of commonly used reliability indices in sports medicine and exercise science: a critical review with data simulations. Eur J Appl Physiol. 2025;125(6):1511–26; doi: 10.1007/s00421-025-05720-6.
37.
Cassidy J, Kadlec D, Fransen J. Exploring convergence and divergence in seemingly contrasting perspectives on training perceptual-cognitive abilities for sports performance through moderated dialogue. Sports Med Open. 2025;11(1):101; doi: 10.1186/s40798-025-00904-y.
38.
Chow JY, Davids K, Hristovski R, Araújo D, Passos P. Nonlinear pedagogy: learning design for self-organizing neurobiological systems. New Ideas Psychol. 2011;29(2):189–200; doi: 10.1016/j.newideapsych.2010.10.001.
39.
Headrick J, Renshaw I, Davids K, Pinder RA, Araújo D. The dynamics of expertise acquisition in sport: the role of affective learning design. Psychol Sport Exerc. 2015;16(1):83–90; doi: 10.1016/j.psychsport.2014.08.006.
40.
Seifert L, Hacques G, Komar J. The ecological dynamics framework: an innovative approach to performance in extreme environments: a narrative review. Int J Environ Res Public Health. 2022;19(5):2753; doi: 10.3390/ijerph19052753.
41.
Davids K, Araújo D, Vilar L, Renshaw I, Pinder R. An ecological dynamics approach to skill acquisition: implications for development of talent in sport. Talent Dev Excell. 2013;5(1):21–4.
42.
Heuvelmans P, Di Paolo S, Benjaminse A, Bragonzoni L, Gokeler A. Relationships between task constraints, visual constraints, joint coordination and football-specific performance in talented youth athletes: an ecological dynamics approach. Percept Mot Skills. 2024;131(1):161–76; doi: 10.1177/00315125231213124.
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